Optimal growth temperature hypothesis: Why do anchovy flourish and sardine collapse or vice versa under the same ocean regime?
Bibliographic record
Abstract
The out-of-phase population oscillations between anchovy and sardine have been attributed to climate changes. However, the biological processes causing these species alternations have remained unresolved. Here we propose a simple "optimal growth temperature" hypothesis, in which anchovy and sardine regime shifts are caused by differential optimal temperatures for growth rates during the early life stages. Dome-shaped relationships between growth rate and sea temperature were detected for both Japanese anchovy (Engraulis japonicus) and Japanese sardine (Sardinops melanostictus) larvae based on otolith microstructure analysis. The optimal growth rate for anchovy larvae occurred at 22.0 °C, whereas that for sardine larvae occurred at 16.2 °C. Ambient temperatures have historically fluctuated between these optima, which could lead to contrasting fluctuations in larval growth rates between the two species. This simple mechanism could potentially cause the shifts between the warm anchovy regime and the cool sardine regime in the western North Pacific. Although retrospective analysis suggested synergistic effects of other factors (e.g., trophic interactions and fishing), the optimal growth temperature concept would provide a possible biological mechanism of anchovy and sardine regime shifts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".